Increasing adolescents' depth of understanding of cross‐curriculum words: an intervention study
Bibliographic record
Abstract
BACKGROUND: There is some evidence that vocabulary intervention is effective for children, although further research is needed to confirm the impact of intervention within contexts of social disadvantage. Very little is known about the effectiveness of interventions to increase adolescent knowledge of cross-curriculum words. AIMS: To evaluate the effectiveness of an intervention programme designed to develop adolescents' knowledge of cross-curriculum words. METHODS & PROCEDURES: Participants were 35 adolescents aged between 12 and 14 years who were at risk of educational underachievement with low scores on a range of assessments. Participants received a 10-week intervention programme in small groups, targeting 10 cross-curriculum words (e.g., 'summarize'). This was evaluated using a bespoke outcome measure (the Word Knowledge Profile). The study involved an AABA design, with a repeated baseline, delayed intervention cohort and blind assessment. Intervention included both semantic and phonological information about the target words and involved the adolescents using the words in multiple contexts. OUTCOMES & RESULTS: Results were promising and participants' knowledge of the targeted words significantly increased following intervention. Progress was demonstrated on the Word Knowledge Profile on the item requiring participants to define the word (for the summer intervention group only). This increase in depth of knowledge was seen on taught words but not on matched non-taught words. CONCLUSIONS & IMPLICATIONS: Cross-curriculum words are not consistently understood by adolescents at risk of low educational attainment within a low socio-economic context. A 10-week intervention programme resulted in some increases to the depth of knowledge of targeted cross-curriculum words.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".